Analyzing Network Connections...
Network Profile
How is this calculated?
The math continuously tracks how strongly this post is connected to the rest of the network. Every tag forms a 2-way link. The base stats determine personal node strength, and the pie charts below show this node's share against its direct neighbours.
// 1. Base variables (floored at 1 to prevent zero-multiplication math errors)
$inbound = max(1, 2) = 2
$outbound = max(1, 2) = 2
// 2. Node Base Values (Local connection strength)
Base_Strength (PV) = $inbound * $outbound = 2 * 2 = 4
Base_Influence (IV) = $inbound / $outbound = 2 / 2 = 1
// 3. Exponential Network Values (accumulating 12 direct neighbours)
Network_Strength (CV) = Base_PV * (Neighbour_1_PV * Neighbour_2_PV * ...)
= 4 *
( 49 [Minus the Bear] *
1 [Alex Rose] *
1 [Cory Murchy] *
49 [Jake Snider] *
1 [Matt Bayles] *
4 [David Knudson] *
36 [Botch] *
9 [Dave Verellen] *
1 [Tim Latona] *
1 [David Verellen] *
72 [Erin Tate] *
20 [Brian Cook (2)]
)
= 17.92B
Network_Influence (TV) = Base_IV * (Neighbour_1_IV * Neighbour_2_IV * ...)
= 1 *
( 1 [Minus the Bear] *
1 [Alex Rose] *
1 [Cory Murchy] *
1 [Jake Snider] *
1 [Matt Bayles] *
1 [David Knudson] *
1 [Botch] *
1 [Dave Verellen] *
1 [Tim Latona] *
1 [David Verellen] *
0.8889 [Erin Tate] *
0.8 [Brian Cook (2)]
)
= 0.7111
Outbound
2
Tags on post
Inbound
2
Posts tagging this
Connections
12
Total nodes
Base Node Strength
4
Base Node Influence
1
Strength Share (vs Direct Neighbours)
Dominant nodes (excluded from chart)Erin Tate 29.03%
Influence Share (vs Direct Neighbours)
Connected Network Hierarchy
Sort list by:
Connection Health Audit (Red = broken 1-way link)
Last calculated: Sep 9, 10:54 PM
King County, United States
31
Related Content
No related content found.